Systems and methods for optimizing travel time using route information

ABSTRACT

A power management system includes a sensor interface that receives sensor data samples during operation of a vehicle. A storage device stores the sensor data samples for multiple points in time along a route segment traveled by the vehicle. One or more processors analyze the sensor data samples to detect a historical pattern of the vehicle. The one or more processors determine time efficient operational parameters for the vehicle in response to a destination and an estimated travel time to the destination. The estimated travel time may be based on predicted conditions of the vehicle indicated by the historical pattern. The time efficient operational parameters may be selected to decrease the estimated travel time. At least one of the sensor data samples may include telemetry data.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.15/705,527, filed Sep. 15, 2017, naming as first inventor MartinKoebler, titled “Optimizing Travel Time Using Route Information,” whichin turn is a continuation of U.S. application Ser. No. 15/626,676, filedJun. 19, 2017, naming as first inventor Martin Koebler, titled “RemoteUpdates for Vehicle Systems,” which in turn is a continuation of U.S.application Ser. No. 14/566,848, filed Dec. 11, 2014, now U.S. Pat. No.9,682,624, naming as first inventor Martin Koebler, titled “PowerManagement using Route Information for a Hybrid Electric Vehicle,” whichin turn is a continuation of U.S. application Ser. No. 14/206,138, filedMar. 12, 2014, now U.S. Pat. No. 8,972,162, naming as first inventorMartin Koebler, titled “Power Management Systems and Designs,” which inturn is a continuation of U.S. application Ser. No. 13/066,189, filedApr. 8, 2011, now U.S. Pat. No. 8,712,650, naming as first inventorMartin Koebler, titled “Power Management Systems and Designs,” which inturn is a continuation-in part of U.S. application Ser. No. 11/283,137,filed Nov. 17, 2005, now U.S. Pat. No. 7,925,426, listing as firstinventor Martin Koebler, titled “Power Management Systems and Devices,”each of which is hereby entirely incorporated herein by reference.

FIELD OF THE INVENTION

The invention relates to devices, methods and systems for controllingpower applied to a vehicle engine.

BACKGROUND OF THE INVENTION

Currently, drivers of automotive vehicles have only very imprecisemethods for managing the fuel consumption of their cars. For example,drivers can slow down, they can brake lightly, and they can carrylighter loads. Generally, however, fuel consumption cannot be preciselycontrolled by the driver. More accurate and precise control of fuelconsumption is one of the best ways to improve the energy efficiency ofmost cars. In particular, accurate control of fuel consumption mayoptimize the energy efficiency of a car.

It has been shown that you can reduce fuel usage by efficient driving.According to Amory Lovins of the Rocky Mountain Institute, a 35%improvement in miles per gallon (mpg) for all 2001 vehicles (whoseoverall average mpg was 20) would have reduced oil use in the UnitedStates by 2.7 Mbbl/d, approximately the same amount that the U.S.imported from the Gulf. See, for example, “Winning the Oil Endgame,”Rocky Mountain Institute, 2004. p. 50. Empirical evidence also supportsthe assertion that efficient driving can reduce fuel usage. For example,the HONDA INSIGHT, a car available to the general public that normallygets 60 mpg, broke records in 2000 by getting 102 miles per gallon in a7-day drive around the circumference of Britain. The team responsibledid this purely by driving more efficiently, and not by modifying thecar in any manner.

In most automotive vehicles, an operator controls the power applied tothe vehicle (e.g., the engine of the vehicle) by operating the ignition,brake and gas pedals. Additional control is typically provided byoperational assisting devices, such as a cruise control, that help tokeep the vehicle at a constant speed, or within a range of speeds.However, such operational assisting devices typically do not optimizethe power consumption of the vehicle, or control the speed and/or powerprovided to the vehicle based on an optimal power consumption level.

Many parameters may impact the optimal power consumption of a vehicle,including external factors (e.g., forces and conditions that act on thevehicle), internal conditions (e.g., the current status of the vehicleand its component parts), operator commands (e.g., control commands fromthe operator driving or preparing to drive the vehicle), and operationalparameters of the vehicle (e.g., performance capabilities of the vehiclebased on the make and model and/or the component parts of the vehicle,as well as the historical performance of the vehicle).

In recent years the need for energy efficient vehicles has increased asthe cost and availability of traditional fossil fuels has fluctuated.However, the need for fuel efficiency spans all types of vehicles,including currently available vehicles (e.g., internal combustion,solar, electric, and hybrid vehicles), as well as vehicles proposed orunder development (e.g., hydrogen fuel cell vehicles and otherelectrically-fueled vehicles). In all of these types of vehicles, theoverall fuel efficiency (regardless of the type of fuel), can beimproved by optimizing the power supplied to the engine. As describedherein, energy efficiency may be fuel efficiency or power efficiency.Energy supplied to the vehicle (e.g., the engine) may come from anyappropriate source (e.g., gas, solar, battery, hydrogen, ethanol, etc.).

Thus, there is a need for devices and systems for controlling the powerapplied to a vehicle engine. The devices, systems and methods describedherein address many problems identified for controlling the powersupplied to automotive engines raised above.

SUMMARY OF THE INVENTION

Described herein are devices, systems, and methods for managing thepower consumption of an automotive vehicle, and thereby for optimizingthe power consumption of the vehicle. The devices and systems formanaging the power consumption of the vehicle typically include powermanagement logic that can calculate an applied power for the vehicleengine based on information provided from the external environment ofthe vehicle, the operational status of the vehicle, one or more commandinputs from a driver, and one or more operational parameters of thevehicle. The information provided to the power management logic may comefrom data inputs (e.g., sensors, telemetries, etc.), memory, usercommands, or it may be derived. The power management logic may comprisesoftware, hardware, or any combination of software or hardware. In somevariations, the devices and systems include a processor (e.g., amicroprocessor) that can perform the power management logic, and providean applied power. The applied power that is determined by the powermanagement logic may be used to control the vehicle engine. For example,the power management logic may be used by a motor control mechanism tocontrol the application of power to the vehicle engine as the vehicletravels along a route (either a predetermined or a non-predeterminedroute). The applied power may also be expressed as an optimized speed orspeeds to which the vehicle is controlled. For example, the motorcontrol mechanism may adjust the speed of the vehicle to an optimizedspeed or speeds as the vehicle travels. Or, the device or system mayprovide a suggested fuel-efficient speed to the driver, who in turn willmanually adjust his/her speed. Thus, the devices, systems, and methodsdescribed herein may optimize the power consumption of an automotivevehicle by controlling the final speed of the vehicle, for example, bycontrolling the power applied to the vehicle motor.

The system may be manually engaged by the operator either when thevehicle is turned on, or in the midst of a trip (e.g., “on the fly”). Inone variation, the operator sets a preferred speed, and a range at whichto manage that speed (e.g., the preferred speed may be 60 mph, and therange can be 5 mph) over at least a portion of the trip. The system maydetermine an optimal (e.g., fuel efficient) speed within the rangeselected. By calculating and then averaging the efficient speed over agiven route, the system can optimize energy usage within the driver'sstated speed and range. The power management logic may determine energyefficiency over the course of a trip, based on current location anddestination. The destination of the driver does not have to be known(e.g., input into a GPS or other similar system by the driver). Thesystem (e.g., anticipated destination logic) may infer the driver'sdestination based on a subset of the information inputs to the system,such as the time of day, current location, previous driving habits, andother inputs. In some variations, the driver can manually accelerate(e.g., override the system) for passing, braking and the like. In somevariations, the device or system may provide a suggested speed to thedriver to match, in order for the driver to better optimize power usage.

In some variations, the system is automatically enabled whenever thevehicle is turned on. In this case, the operator of the vehicle does nothave to set any destination, target speed or range, or the like. Byautomatically monitoring the operator's real-time speed, braking andacceleration, and by utilizing applicable inputs (e.g., from sensorsand/or from a database), the power management system may determine themost efficient speed to travel a route. In some variations, the deviceor system may adjust the vehicle speed automatically. The powermanagement devices or systems described herein may operate whether ornot the driver has entered a destination into the GPS, because thesystem may infer the destination based on previous driving habits if thedriver has not explicitly provided a destination.

In some variations, the driver (or other user) provides the system adestination and the vehicle determines the optimal speeds to drivethroughout the route. The system may use speed limits, trafficconditions, physical calculations, and statistical models from previoustrips to the same destination to select the target speeds to optimizearound. Thus, in some variations, the driver only needs to steer,although hard acceleration or braking by the driver may override thesystem.

Described herein are devices for managing the power consumption of anautomotive vehicle comprising a power management logic operable tocalculate an applied power for the vehicle engine from information aboutthe external environment of the vehicle, information about theoperational status of the vehicle, one or more command inputs, and oneor more operational parameters of the vehicle. The power managementdevice may also include a processor responsive to the power managementlogic (e.g., a microprocessor), and a motor control mechanism, whereinthe motor control mechanism controls the application of power to thevehicle engine.

The power management logic may determine an applied power for thevehicle engine based on information about the external environment ofthe vehicle that is selected from the group consisting of: the currentlocation of the vehicle, the elevation of the vehicle, upcomingelevations of the vehicle, the current slope/grade of the route, thepredicted slope/grade of the next segments (or upcoming segments) of theroute, speed limit information of the current route segment, speed limitinformation of upcoming route segments, the condition of the known orpredicted route (or a portion thereof), traffic information or data,traffic surrounding the vehicle, the location of stoplights, the timingof stoplights, a map of the roadway, the present angle of the sun, thepredicted angle of the sun for upcoming route segments, the weatheraround the vehicle, present wind direction, the predicted wind directionfor upcoming route segments, present wind velocity, the predicted windvelocity for upcoming route segments, current temperature, the predictedtemperature for upcoming route segments, current air pressure, predictedair pressure for upcoming route segments, time of day, date, day ofweek, visibility, present road conditions, predicted road conditions forupcoming route segments, and the distance to/from other vehicles. Any ofthis information may be acquired by measuring (e.g., from sensors), orit may be detected or input (e.g., from manual inputs, telemetry,detectors, a memory, etc.), or it may be derived (e.g., based on otherinformation, including other environmental information).

The power management logic may determine an applied power for thevehicle engine based on information about the operational status of thevehicle. The operational status information input may be selected fromthe group consisting of: the vehicle's current speed, the motor speed,the vehicle's current orientation, the RPM of the vehicle's motor, wheelrotations per minute, the battery state, the voltage of the battery, theamp hours from the battery, the state of the battery, the temperature ofthe battery, the age of the battery, and the number of times the batteryhas charged and discharged, the tire pressure, the drag force due torolling resistance of the vehicle, the weight of vehicle, the amount ofair going to the engine, the amount of gas going to the engine, and theweight of the driver. Any of this information may be acquired bymeasuring (e.g., by sensors), or it may be input (e.g., from an externaltelemetry, a memory, etc.), or it may be derived (e.g., based on otherinformation, including other operational status information).

The power management logic may determine an applied power for thevehicle engine based on command input information. Command inputinformation may be selected from the group consisting of: theacceleration applied by a driver, the braking applied by a driver, theintended destination, preferred speed, maximum and minimum range overwhich speed should adjust, and preferred route. Any of this informationmay be acquired by input (e.g., from an external telemetry, keyboard,mouse, voice command, a memory, etc.), sensor (e.g., optical detectors,etc.), or it may be derived (e.g., based on other information, includingother command information).

The power management logic may determine an applied power for thevehicle engine based on information about one or more operationalparameters of the vehicle. Operational parameters may be selected fromthe group consisting of: aerodynamic parameters (CDA), rollingresistance parameters (Crr1 and Crr2), drive train efficiencyparameters, motor efficiency parameters, battery model parameters,battery charge and discharge relationships, and type of battery. Any ofthis information may be input (e.g., from an external telemetry, amemory, etc.), or it may be derived (e.g., based on other information,including historical information or other operational parameterinformation).

The power management device or system may further comprise a memorycontaining vehicle information about one or more operational parametersfor the vehicle. The memory may store any of the information about theexternal environment, operational status or command inputs, includingderived or historical information.

The devices and systems described herein may be used with anyappropriate vehicle, including internal combustion vehicles (which runon gasoline, diesel, or ethanol for example), hybrid internalcombustion/electric vehicles, electric vehicles powered by the electricgrid (plug-in), electric vehicles powered by the sun (solar), andhydrogen fuel cell vehicles.

Also described herein are systems for managing the power consumption ofan automotive vehicle, comprising a first input, operable to receiveinformation about the external environment of the vehicle, a secondinput, operable to receive information about the operational status ofthe vehicle, a third input, operable to receive one or more commandinputs from a driver of the vehicle, a memory containing informationabout one or more operational parameters of the vehicle, powermanagement logic operable to calculate an applied power for the vehicleengine from the first input, the second input, the third input, and thememory, and a processor responsive to the power management logic. Thesystem may also include a motor control mechanism, wherein the motorcontrol mechanism regulates the application of power to the vehicleengine.

Also described herein are methods of managing the power consumption of avehicle, including calculating an applied power for the vehicle using aprocessor. The processor (e.g., a microprocessor, etc.) receives a firstinput comprising information about the environment of the vehicle, asecond input comprising information about the operational status of thevehicle, a third input comprising a command input from the driver of thevehicle, and a fourth input comprising vehicle information about theoperational parameters of the vehicle. The method may also include thestep of applying the applied power to the engine of the vehicle, and/ornotifying the driver of the optimal speed.

The step of calculating an applied power may include determining aroute, segmenting the route into one or more segment (or intermediate)destinations, calculating an energy efficient speed for the vehicle totravel to the segment destination, determining an optimized speed forthe vehicle to travel to the segment destination, and calculating theapplied power from the optimized speed for all of the segments. Theapplied power may be calculated continuously. For example, the appliedpower may be calculated at each point (e.g., every segment, or pointswithin a segment) as the vehicle is driven. Thus, over an entire route,the most energy efficient speed at which to drive may be continuouslycalculated. This may be done by determining a destination, and thencoming up with a route for that destination. If the destination is notknown (e.g., has not been provided to the power management device orsystem), a predicted destination may be estimated, based on statisticaldestination logic (e.g., using map coordinates, and the historicaloperation of the vehicle). Energy efficient speeds for current andupcoming route segments can then be calculated based on the route. Insome variations, the route is divided up into segments. In somevariations, the optimized speed for the vehicle is determined based onhistorical speeds for similar destinations. The route can be revised(e.g., continuously revised) during operation.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A, 1B show an example of a vehicle controlled by a traditionalcruise control device and the same vehicle controlled by one variationof this power management system described herein.

FIG. 2 illustrates steps that may be used to optimize power applied to amotor, as described herein.

FIG. 3A shows a schematic route as described herein.

FIG. 3B shows steps that may be followed to determine a routedestination.

FIGS. 4A, 4B show steps that may be followed to determine a calculatedoptimized velocity for segments of a route.

FIG. 5 shows steps that may be followed for determining a probableoptimal speed based on historical route information.

FIG. 6 shows a schematic diagram of one variation of the powermanagement logic described herein.

FIG. 7 illustrates one variation of a vehicle including a powermanagement system, as described herein.

FIG. 8 illustrates a user interface for a power management device.

FIG. 9 shows inputs that may be coordinated by the power management userinterface.

FIG. 10 shows a schematic diagram of a portion of a power managementsystem, as described herein.

FIG. 11 illustrates a power management system remotely communicatingwith a server, as described herein.

FIGS. 12A, 12B show exemplary charge and discharge characteristics forone type of battery.

FIGS. 13A, 13B show examples of engine characteristics.

DETAILED DESCRIPTION

The power supplied and used by a motorized vehicle can be optimizedbased on information inputs including: user demands, environmentalconditions, the current or anticipated operational state of the vehicle,and the operational parameters for the vehicle. These parameters can beestimated, directly measured, or derived, and may be used to determinethe driving route, and therefore an estimated power requirement for theroute. The estimated power requirement for a route and a historicalpower requirement from the same vehicle traveling over the same routemay be used to determine the optimal power supplied to the vehicle. Thepower required of a vehicle and the optimal power supplied to a vehiclemay also be expressed in terms of the speed or velocity of the vehicle.

Management of a vehicle's power supply typically involves optimizationof the power supplied to the engine. As described herein, the “engine”may refer to any portion of the vehicle to which power is supplied,including the motor, powertrain, etc. As will be apparent below,optimizing the power supplied to the engine typically means minimizingthe energy loss from the vehicle, thereby increasing fuel efficiency.The power supplied to the engine may alternatively be optimized based onother criterion. For example, the power supplied to the engine may beoptimized with respect to speed or travel time. Furthermore, thedevices, methods and systems described herein may be used with anyappropriate vehicle, and are not limited to internal combustionvehicles. For example, the devices, methods and systems described hereinmay be used with vehicles having a hybrid internal combustion/electricengine, an electric engine powered by the electric grid (e.g., a plug-invehicle), an electric engine powered by the sun (e.g., a solar vehicle),and an electric engine powered by hydrogen fuel cell. Thus the term“fuel” does not necessarily refer exclusively to hydrocarbon fuels, butmay refer to any appropriate power source for the engine.

FIGS. 1A and 1B compare a traditional “cruise control” device (in FIG.1A) to one variation of the power management device described herein (inFIG. 1B). In FIG. 1A, a typical cruise control device regulates thespeed of a vehicle as it drives from point A to point B when the vehiclespeed is set to 50 mph. As the vehicle moves across different terrain(e.g., roads having different elevations), or through different weatherconditions, the traditional cruise control device adjusts the powersupplied to the vehicles (and thus the speed) based only on the setvelocity and the actual velocity of the vehicle. Thus, the cruisecontrol device receives information on the current speed of the vehicle,and adjusts the power supplied to the engine to maintain the vehicle atthe set speed. This type of device is a “velocity control” cruisecontrol device. In contrast, FIG. 1B shows a vehicle with a powermanagement device for optimizing the power supplied to the vehicle, asdescribed further herein.

In FIG. 1B, the power management system receives external inputs,including information on the location and grade (e.g., steepness of anyuphill/downhill portions) of the road, and the distances traveled. Thepower management system also includes or deduces information about theroute (e.g., from point A to point B), and the acceptable range ofspeeds that the vehicle may travel over this route (e.g., between 45 and55 mph). The power management system may also receive information aboutthe state of the vehicle, including the velocity at which it istraveling, and the weight of the vehicle. Finally, the power managementsystem may include operational parameters such as the performance of theengine, aerodynamic performance, and rolling resistance of the vehicle.Given this information, the power management system may calculateapplied power to the engine, and may derive a speed (or set of speeds)that optimizes the applied power. As shown in FIGS. 1A and 1B, the totalenergy used by the power management system in FIG. 1B is 0.9 kwhcompared to 1 kwh for the cruise control system shown in FIG. 1A foridentical vehicles traveling over the same pathway.

In general, there are many ways to optimize energy efficiency, asdescribed in more detail below. As will be described, any of themethods, devices and system described herein may be used together,individually, or in different combinations.

Inputs

The power management devices and systems described herein manage thepower of the vehicle using inputs from four categories of informationinput: information from the external environment of the vehicle,information about the operational status of the vehicle, informationfrom one or more command inputs, and operational parameters of thevehicle. Typically, at least one input from each of these sources ofinformation is used to determine an optimal speed (or applied power) forthe vehicle. Some of the information inputs for each of these categoriesare described below. In every case, the information may be directlymeasured (e.g., by sensors or other inputs), communicated from anexternal source, or it may be derived from other information inputs, orfrom stored data.

Information from the external environment of the vehicle may be used todetermine the optimal power to apply to the vehicle. Externalenvironment information generally includes any information about theenvironment surrounding or acting on the vehicle. External informationmay be used to determine forces acting on the vehicle (e.g., drag, windresistance, tire resistance, etc.), the location of the vehicle relativeto the destination (e.g., position, direction, etc.), and theenvironment surrounding the vehicle (e.g., traffic patterns, surroundingtraffic, etc.). In some variations, the external information may be usedto help describe the power available to the vehicle, particularly insolar powered vehicles (e.g., amount of light energy, time of day,position of the sun, etc.).

Examples of environmental information inputs include, but are notlimited to: the current location of the vehicle, geographicalinformation about the surrounding area, the elevation of the vehicle,upcoming elevations of the vehicle, the current slope/grade of road, thepredicted slope/grade of the next segments of road, traffic surroundingthe vehicle, the location of stoplights, the timing of stoplights, a mapof the roadway, the present angle of the sun, the predicted angle of thesun for upcoming route segments, the weather around the vehicle, presentwind direction, the predicted wind direction for upcoming routesegments, present wind velocity, the predicted wind velocity forupcoming route segments, current temperature, the predicted temperaturefor upcoming route segments, current air pressure, predicted airpressure for upcoming route segments, time of day, date, day of week,visibility, present road conditions, predicted road conditions forupcoming route segments, and the distance from other vehicles.

Some of the information inputs may be redundant, or may be derived fromrelated information. For example, the vehicle location may be providedby a GPS device which may be either a separate device or a portion ofthe power management device that receives a GPS signal and locates thevehicle based on the received signal. Geographical and topographicalinformation about the area surrounding the vehicle may be determinedfrom the location information. For example, the location may be used toindex an atlas of the surrounding area. Some variations of the powermanagement device include a memory or database of information, includinginformation about maps and road information. In some variations, thepower management device communicates with one or more such databases toidentify the location and surrounding road features (e.g., suggestedspeed limits, stop signs, traffic patterns, etc.).

The power management device may include or may be connected to sensorsor other inputs to directly determine some of the information inputs.For example, the power management device may include a pre-set clock(e.g., for the current time and date), one or more optical sensors(e.g., to determine the intensity of sunlight, visibility, distance fromnearby vehicles, etc.), and/or weather sensors (e.g., temperature, winddirection and velocity, air pressure, etc.). In some variations, thepower management system receives some of this information by telemetrywith off-board information sources such as databases and the like. Forexample, the power management system may communicate with a weatherservice, a map service, a traffic service, etc.

These examples of information about the external environment are onlyintended to illustrate the kinds of external information that may beused by the power management devices and systems described herein andare not intended to be limiting. Any appropriate information about theexternal environment may be provided to the power management device orused by the power management device.

Information about the operational status of the vehicle may be used todetermine the optimal power to apply to the vehicle. Operational statusinformation generally includes any information about the currentoperational status of the vehicle itself. Operational status informationmay be used to determine the current condition of the vehicle's engineand component parts (e.g., motor, powertrain, battery, tires, etc.), thecurrent fuel supply, the manner in which the vehicle is traveling (e.g.,velocity, acceleration, etc.), and the like.

Examples of environmental information inputs include, but are notlimited to: the vehicle's current speed, the motor speed, the vehicle'scurrent orientation, the RPM of the vehicle's motor, wheel rotations perminute, the battery state, the voltage of the battery, the amp hoursfrom the battery, the state of the battery, the temperature of thebattery, the age of the battery, the number of times the battery hascharged and discharged, the tire pressure, the drag force due to rollingresistance of the vehicle, the weight of vehicle, the amount of airgoing to the engine, the amount of gas going to engine, and the weightof driver.

As described above, some of the information inputs may be redundant, ormay be derived from related information. Furthermore, the powermanagement system may use any of the sensors, gauges and detectorsalready present in the vehicle as information inputs. For example, thevelocity of the vehicle may be detected by a speedometer which may passinformation on to the power management system. The power managementdevice may also include additional sensors, inputs or detectors todetermine or derive any information about the operational status of thevehicle. For example, the power management device or system may includeone or more weight sensors (to determine the load in the vehicle,including the driver's weight).

The examples of operational status information inputs are only intendedto illustrate the kinds of operational status information that may beused by the power management devices and systems described herein. Anyappropriate information about the operational state of the vehicle maybe provided to the power management device or used by the powermanagement device.

Information from one or more command inputs may be used to determine theoptimal power to apply to the vehicle. Command inputs generally includeany instructions from the driver of the vehicle about the operation (orintended operation) of the vehicle. Command inputs may be directly inputby the user, or they may be derived by the actions of the driver or theidentity of the driver.

Examples of command inputs include, but are not limited to: theacceleration applied by a driver, the braking applied by a driver, thevehicle's known or predicted final destination, the vehicle's known orpredicted interim destination, preferred speed, maximum and minimumrange over which speed should be adjusted, and preferred route.

As with all of the information inputs, some of the command inputs may beredundant, or may be derived from related information. For example, aroute destination may be input by the driver, or it may be inferred fromthe driving behavior and/or identity of the driver. The identity of thedriver may also be input by the driver, or it may be inferred. Forexample, the identity of the driver may be matched to the weight of thedriver. Command inputs may include any of the driver's actions tocontrol the vehicle. For example, command inputs may include steering,braking, shifting, or application of the accelerator. The powermanagement device may include sensors, inputs or detectors to monitorthe manipulations of the driver. In some variations, the driver maydirectly input commands to the power management system or to otherdevices in the vehicle that communicate these command to the powermanagement system. For example, the driver may use an on-boardnavigational system to select a destination, and this destination may becommunicated to the power management system. In some variations, theuser may provide commands directly to the power management system. Insome variations, the command inputs may be derived from otherinformation, including the environmental information and the operationalstatus information. For example, the destination (either a final or anintermediate destination) may be estimated based on the current locationof the vehicle, the direction that the vehicle is traveling, the time ofday and/or the driver of the vehicle (e.g., if it's 8:00 am, and driverX is driving the car on interstate 280, then the final destination ismost likely to the address of X's work place).

Information inputs, including command inputs, may have default orpre-set values. For example, the power management device or system mayhave a preset or default maximum and minimum range of speeds fortraveling part of the route (e.g., if the maximum and minimum range hasnot been explicitly input, the maximum and minimum range may be set to+/−4 mph). In some variations, the information inputs may includemetadata describing one or more features of an information input.Metadata may include information about the information input. Forexample, metadata may indicate the last time a particular data input wasupdated, or may indicate that the data is a default setting, or thelike.

These examples of command inputs are only intended to illustrate thekinds of command inputs that may be used by the power management devicesand systems described herein. Any appropriate command input may beprovided to the power management device or used by the power managementdevice.

Information from one or more operational parameters of the vehicle maybe used to determine the optimal power to apply to the vehicle.Operational parameters generally include information aboutcharacteristics that are specific to the vehicle (e.g., characteristicsof component parts of the vehicle, including the battery, the engine,the powertrain, the tires, etc.). Operational parameters of the vehiclemay be stored and retrieved from a memory that is part of the powermanagement device or system, or they may be retrieved from a remoteinformation source.

Examples of operational parameters include, but are not limited to:aerodynamic parameters (CDA), rolling resistance parameters (Crr1 andCrr2), drive train efficiency parameters, motor efficiency parameters,battery model parameters, battery charge and discharge relationships,and type of battery.

The operational parameters may be fixed (e.g., may not vary withoperation of the vehicle), or they may be changed. In some variations,the operational parameters may comprise a database (e.g., a lookuptable), so that the value of the operational parameter may depend uponanother information input, and may be retrieved from the database byusing one or more information inputs as a search key. In somevariations, the operational parameter may comprise an equation orrelationship that has other information inputs as variables.

Examples of operational parameters are provided below. In general,operational parameters may be determined experimentally (e.g., bytesting) or may be provided by product manufacturers. In somevariations, general (or generic) operation parameters may be used ifmore specific parameters are not available. For example, battery chargeand discharge graphs (showing operational characteristics of thebattery) can be obtained from battery manufacturers. Operationalparameters for various types of batteries (e.g., Lithium polymerbatteries, etc.) can include material characteristics, energy densities,power densities, thermal characteristics, cycle life, charge anddischarge characteristics (e.g., voltage over time), and current fluxover time. For example, FIGS. 12A and 12B show exemplary charge anddischarge characteristics for one type of Lithium polymer battery (e.g.,the Li—Po 40 Ah from LECLANCHE SA, Switzerland). Completecharacterization may also be made by taking charge and dischargemeasurements from either a specific battery, or a specific model andmake of a battery.

Motor efficiency data may be obtainable from the manufacturer. A fullmodel dynamometer testing may also be used to determine motorcharacteristics. For example, FIGS. 13A and 13B show some examples ofmotor characteristics that may be provided. Aerodynamic parameters ofthe vehicle (e.g., the outer chassis) can also be provided by the automanufacturer, or could be measured (e.g., in a wind tunnel). Aerodynamicproperties may also be estimated or calculated for different vehicles(or vehicle shapes, makes, or models) using literature values. Examplesof aerodynamic parameters may be found, for example in “GM SunraycerCase History/M-101” (Published by the Society for Automotive Engineers,Inc, Dec. 1, 1990), The Leading Edge: Aerodynamic Design ofUltra-Streamlined Land Vehicles (Engineering and Performance) by GoroTamai (Robert Bentley, Inc, 1999), and The Winning Solar Car: A DesignGuide for Solar Race Car Teams by Douglas R. Carroll (SAE International,2003), each of which is herein incorporated by reference in itsentirety. Examples of drag coefficients are also readily available(e.g., online: http://www.answers.com/topic/drag-coefficient-1, lastvisited Oct. 12, 2005).

Rolling resistance parameters may also be provided by the tiremanufacturer, or may be measured. An example of one variation of apublished rolling resistance formula may be found in “Fahrwerktechnik:Reifen and Raeder” by Jornsen Reimpell and Peter Sponagel (published byVogel-Fachbuch Technik, ISBN 3-8023-0737-2, 1988), herein incorporatedby reference in its entirety. Similarly, a drivetrain efficiency modelmay be provided by the vehicle manufacturer, or may be measured from thepower input vs. the power output for the entire drivetrain. Somevariations (e.g., some variations of solar cars, for example) do nothave a drivetrain, since the motor is built directly into the wheel.

Examples of operational parameters are only intended to illustrate thekinds of operational parameters of the vehicle that may be used by thepower management devices and systems described herein. Any appropriateoperational parameter may be provided to the power management device orused by the power management device.

The information inputs described herein may be used to determine theoptimally efficient energy to supply to the engine.

Optimization of Engine Efficiency

FIG. 2 illustrates some of the steps that may be followed to optimizethe energy supplied to an engine so that the vehicle travels at afuel-efficient speed. To determine an optimally efficient speed (or theoptimal power to be supplied to the engine), a route is determined 201from the starting position and an actual or estimated ending position,the route is segmented 203 into one or more segments, a model optimalspeed (or power) is calculated 205, statistical data from previous tripsalong the same segment of the route are retrieved 207, and an overallefficiency applied power is calculated from at least the model power andthe statistical data 209. Finally, the overall efficient applied poweris provided to the engine. In some variations, the vehicle operator maybe notified of the overall efficient applied power instead of (or inaddition to) automatically applying this optimal power. Each of thesesteps is described more fully below. The statistical data from previoustrips may be an optional element. For instance, one may choose not theuse statistical data or one may not have statistical data.

1. Determine Route

The route is determined based on the current position of the vehicle anda final destination position. The destination position may be explicitlyprovided by the operator of the vehicle (e.g., as an operator input), orit may be derived. In some variations, the operator may provide adestination directly to the power management device, or to a device thatcommunicates with the power management system (e.g., an on-boardnavigation system, etc.). The operator may also select the preferredroute to the final destination either before beginning the trip, orafter beginning the trip. For example, the operator may choose adestination using a navigation system including navigation systems thatare not part of the power management device (such as any commerciallyavailable GPS navigation system), which may also generate a route. TheGPS navigation system may communicate the destination and routeinformation to the power management device. In some variations, thepower management system includes a GPS component or module, and may atleast partly act as a navigation system.

The destination may be derived from information about the operator, thecurrent location, the time of day, or the like. The power managementdevice may include statistical destination logic that determines one (ormore) most likely destinations based on information provided fromenvironmental inputs, user command inputs, and vehicle operationalstatus inputs. In some variations, the destination is derived bygenerating a series of statistically weighted (e.g., likely)destinations based on any, all, or some of these inputs. Examples ofsome of the inputs that may be used by the statistical destination logicto determine a likely destination may include, but are not limited to:the weight of the driver, the time of the day, the current location ofthe vehicle, the direction that the vehicle is facing (or traveling in),the day of the week, and the speed of the vehicle.

The statistical destination logic may identify one or more destinationsbased on information held in a memory. For example, the statisticaldestination logic may use any of the information inputs to select amonga record of destinations to which the vehicle has previously driven.These destinations may be assigned a probability weighting based on theinformation inputs. For example, the statistical destination logic maycontinuously infer the vehicle's destination. The information inputs canbe used to assign a probability to a particular destination. It isimportant to note that the word “destination” in this context is notnecessarily the driver's final destination. It may be an intermediatedestination along the route that the statistical destination logicdetermines has a greater chance than some threshold likelihood (e.g., X%) of being the destination. A threshold likelihood may be preset, andmay be varied by the user or by the power management device.

For instance, if a driver leaves her house to go to work, and drivestoward the highway, the statistical destination logic may determine thatthere is a 95% chance that she is going to the highway but only a 75%chance that she is going to go South on the highway. So, if thethreshold (X) is 90%, the “destination” in this case would be thehighway onramp. Once she gets on the highway going south, theprobability that she is going to work may have increased to 92%. Now,the “destination” would be her work. Thus, as the vehicle drives around,the probable destination determined by the statistical destination logicmay constantly change to revise the destination or intermediatedestination.

In some variations, the statistical destination logic accesses (and mayalso write to) a memory comprising past destinations that are correlatedto some or all of the information inputs (such as location, driverweight, time of day, day of week, direction, velocity, etc.), and/orinformation derived from these inputs (e.g., driver identity, drivinghabits, etc.). The list of possible locations may be weighted by thestatistical destination logic based on how closely the informationinputs correspond to the associated information inputs for thesedestinations, and may be influenced or refined by the number of timesthat the driver has driven to this destination. Some of the informationinputs (or some combination of the information inputs) may be weightedmore heavily than others in determining the likelihood of a destination.Furthermore, the statistical destination logic may select more than onelikely destination, including selecting a final destination and one ormore intermediate destinations.

One variation of a procedure for determining the most likely destinationis described below, and illustrated in FIG. 3B. For example, theschematic route shown in FIG. 3A has 10 junctions (A to J). Theprobability that a driver will take any particular route from the startposition may be described as “P”. Thus, Pold is the previous (or old)percentage likelihood of taking a route, whereas P is the newlycalculated percentage likelihood. Pold is initially set to 1 becausethere is a 100% likelihood that your route will go through the placethat you are currently at. As used in this example, an intersection isas a junction having more than one choice of direction that you may goin. Examples include highway exits (e.g., you can stay on the highway ortake the exit), a four-way stop, and a fork in the road.

Referring now to FIG. 3A, assume that you have taken the followingtrips:

1. start→A→C→E

2. start→A→C→D→F

3. start→A→G→I

4. start→A→G→I

5. start→A→C

6. start→A→C→E

7. start→A→C→E

8. start→A→G→J→C→E

9. start→A→C→E

10. start→A→C→D→F

Based on this trip history, the probability of your moving from anyjunction in the route shown in FIG. 3A can be determined. Theseprobabilities are tabulated in the table:

Probability of Probability of going continuing in the through eachlocation Position possible directions based on past behavior start 10/10A A 7/10 C A: 10/10 = 100% 3/10 G 0/10 B B 0/0 B: 0/0 = 0% C 2/8 D C:(10/10)*(7/10) + 5/8 E (10/10)*(3/10)*(1/3)*(1/1) = 71% 1/8 end D 2/2 FD: (.71)*(2/8) = 17.75% E 5/5 end E: (.71)*(5/8) = 44.375% F 2/2 end F:(.1775)*(2/2) = 17.75% G 2/3 I G: (10/10)*(3/10) = 30% 1/3 J H 0/0 H:0/0 = 0% I 2/2 end I: (.30)*(2/3) = 20% J 1/1 C J: (0.30)*(1/3) = 10%

The Table also shows the probability of going through each locationbased on my previous driving behavior in the next trip. For a new trip,at each junction, the probabilities may be recalculated. For example (onthe same trip), once you have reached point A and decided to turn towardC, the new probabilities are recalculated as: A: 0%, B: 0%, C: 100%, D:25%, E: 62.5%, F: 25%, G: 0%, H: 0%, I: 0%, J: 0%. In real worldexamples, it could take hundreds of drives before the statistics becomeuseful at predicting where the driver is likely to go. FIG. 3Billustrates one variation of a statistical destination logic that may beused.

2. Segment Route

The route used by the power management device typically includes astarting position (e.g., the current position of the vehicle, which maybe indicated by GPS), an ending position, as described above, and anyintermediate positions between the initial and the final positions. Insome variations, the route may be broken up into segments that may beused by a power management device to optimize the power needed to travelthis segment. A segment may comprise any distance to be traveled,including the entire route, or small portions of the route. Differentsegments in the same route may be of different lengths.

The route may be segmented in any appropriate manner. For example, theroute may be broken into segments based on predetermined or anticipatedchanges in speed (e.g., switching from 65 to 55 mph), changing trafficpatterns (e.g., turns, stops, yields, etc.), traffic or anticipatedtraffic, distance (e.g., x miles), terrain (e.g., the gradient orcondition of a road), or the like. In some variations, the route may besegmented based on a combination of such factors.

A route may be entirely segmented, or only partially segmented. Forexample, the power management device may segment only the first part ofthe route (e.g., the portion containing the current position of thevehicle), or the first few segments. This may be particularly usefulwhen the destination is an anticipated destination determined by thestatistical destination logic, for example. The route may becontinuously re-segmented. For example, as the vehicle moves, the powermanagement device may become aware of changing road conditions (e.g.,traffic, weather, etc.), or the user may change the route, necessitatingre-segmenting. As used herein, “continuously” may mean repeated multipletimes, including repeating regularly or periodically.

In some variations, the entire route (or the entire predicted route) maybe divided up into N segments. The number (N) of segments may be fixedor may depend upon the route. The more segments that the route is splitinto, the more accurate the model may be. However, more segments mayalso require more computing power. Thus, the number of segments N may bedecided based on the tradeoff between computing power and accuracy.

3. Calculated Energy for the Route

The power required by the vehicle to travel along a route, or a segmentof the route, may be estimated or calculated, and this calculation maybe used to determine a calculated speed for the vehicle so that thepower usage is optimized or minimized. Such calculations of powerrequirements at different speeds typically use information inputs fromthe vehicle, the user, and the environment over the route from theinitial position to a destination (e.g., a final destination or anintermediate destination). Any appropriate information input may beused.

Simulation of the power requirement of the vehicle may estimate powerrequirements at different speeds. Thus, the speed(s) that the vehicletravels the route (or a segment of the route) can be optimized. Forexample, the simulation could determine the most energy efficient speedfor the vehicle to travel over one or more segments by minimizing thepower requirement for the vehicle while allowing the speed to varywithin the range of acceptable speeds.

In some variations, the power management device includes simulatedenergy requirement logic that determines the power requirement given theinformation inputs (e.g., information from the external environment ofthe vehicle, the operational status of the vehicle, information from oneor more command inputs, and operational parameters of the vehicle). Thesimulated energy requirement logic can calculate the required appliedpower for the vehicle by calculating different power requirements forall or a portion of the route (e.g., the first segment) when the speedof the vehicle is within the range of speeds acceptable for travelingthis section of the route. For example, if the target speed for aportion of the route is 60 mph with a range of +/−5 mph, the simulatedenergy requirement logic may determine the speed at which the energyrequirement is lowest that is closest to the desired speed (60 mph). Anyappropriate method of calculating and/or optimizing this velocity may beused, including iteratively simulating different speeds within thetarget range.

The optimal speed may be calculated by energy calculation logic. Asimplified example is provided below, using the following parameters,assuming an electric car with regenerative brakes.

mass of the vehicle and the driver (m) 4000 kg CdA of the car .25 Therolling resistance coefficients: Crr1 .01 Crr2 .05 Drivetrain efficiency(eff) 80% air density (rho) 1.3 kg/m³ acceleration due to gravity (g)9.8 m/s² number of wheels (n) 4 headwind velocity (vhw) 10 kph or 2.78m/s

In this example, the route may be split into five segments of 5 km eachwith the following altitudes measured at the end of each segment: 0(beginning of segment 1), 200 m (end of 1), 100 m (end of 2), 400 m (endof 3), 100 m (end of 4), 0 (end of 5). We may also make the simplifyingassumption that the road grade is constant between measured points, andthe road grades are calculated to be: +0.04 (seg 1), −0.02 (seg 2),+0.06 (seg 3), −0.06 (seg 4), −0.02 (seg 5). The target average speed is100 kph.

For the sake of simplicity in this example, we can then calculate theamount of energy required to drive at a constant 100 kph speed for theentire route, as well as for 16 other combinations of the speeds 95 kph(26.39 mps), 100 kph (27.78 mps), and 105 kph (29.17 mps). In practice,this simulation may be run for hundreds or even thousands ofcombinations of speeds which may be tested to find the optimal speed todrive each segment. It is assumed that we enter the first segmenttraveling 100 kph (27.78 mps). It is also assumed that the speed listedfor the segment is the final speed of the segment and the vehicleaccelerates linearly throughout the segment.

The Table below shows the results of the energy calculation for all ofthe combinations tried. The lowest energy usage is 4275.94 Watt-hours.This was obtained by going 95 kph (seg1), 105 kph (seg2), 95 kph (seg3),105 kph (seg4), 100 kph (seg5). The average speed over all 5 segments isstill 100 kph, but the energy used is 10.2% less.

iterations seg 1 seg 2 seg 3 seg 4 seg 5 Energy units 1 27.78 27.7827.78 27.78 27.78 4763.2484 Whr 2 26.39 29.17 27.78 27.78 27.78 4536.889Whr 3 26.39 29.17 26.39 29.17 27.78 4275.938 Whr 4 26.39 29.17 26.3927.78 29.17 4382.5026 Whr 5 26.39 29.17 27.78 26.39 29.17 4950.1438 Whr6 26.39 29.17 27.78 29.17 26.39 4438.3467 Whr 7 26.39 26.39 29.17 29.1727.78 4942.6325 Whr 8 26.39 26.39 29.17 27.78 29.17 5055.9124 Whr 926.39 26.39 27.78 29.17 29.17 4784.1865 Whr 10 29.17 26.39 27.78 27.7827.78 5013.2565 Whr 11 29.17 26.39 26.39 29.17 27.78 4745.585 Whr 1229.17 26.39 26.39 27.78 29.17 4852.1495 Whr 13 29.17 26.39 27.78 26.3929.17 5137.6625 Whr 14 29.17 26.39 27.78 29.17 26.39 4914.7142 Whr 1529.17 29.17 26.39 26.39 27.78 4602.8845 Whr 16 29.17 29.17 26.39 27.7826.39 4493.3028 Whr 17 29.17 29.17 27.78 26.39 26.39 4765.4617 Whr

In general, any appropriate relationship between the information inputs,the speed (e.g., the applied power) and the required energy may be usedto determine an optimized speed. In some variations, the energyrequirement may be calculated from aerodynamic information, rollingresistance, potential energy change due to road gradient andacceleration. FIGS. 4A, B show one method of determining the targetspeeds for a route by an iterative method. One variation of a method fordetermining target speeds is described by the equation:

$E = {\frac{V_{tarn}}{eff}\left( {{{CdA}\frac{\rho}{2}\left( {V_{tarn} + V_{hw}} \right)^{2}} + {\left( {{mgC}_{{rr}\; 1} + {{nV}_{tarn}C_{{rr}\; 2}}} \right){\cos\left( {\tan^{- 1}(G)} \right)}} + {{mgsin}\left( {\tan^{- 1}(G)} \right)} + {ma}} \right)}$where E is the total energy used over the segment. The terms of theequation include:

$\frac{V_{tarn}}{eff}$

where V_(tarn)=target velocity over time, and eff is the efficiency ofthe powertrain.

The terms inside of the parentheses calculate the total drag force onthe vehicle. However, we want to calculate the total amount of energy.In general, Power=Force*Velocity, andEnergy=Power*time=Force*Velocity*Time. The total amount of energy usedis increased based on the power lost due to the inefficient powertrain.

The drag force due to the aerodynamics of the car is expressed as:

${CdA}\frac{\rho}{2}\left( {V_{tarn} + V_{hw}} \right)^{2}$where CdA is the coefficient of drag time area (which can be a measuredvalue), and rho (ρ) is the density of air, V_(tarn) is the targetvelocity in the nth iteration, and V_(hw) is the headwind velocity. Thedrag force due to the rolling resistance of the tires is expressed as:(mgC_(rr1)+nV_(tarn)C_(rr2))cos(tan⁻¹(G))where m is the mass of the car, g is the acceleration due to gravity, nis the number of wheels, V_(tarn) is the target velocity in the nthiteration, C_(rr1) and C_(rr2) are the coefficients of rollingresistance, and G is the grade of the road. The coefficients of rollingresistance may be measured values or they may be values supplied bymanufacturers (e.g., a tire manufacturer). The numbers may vary fordifferent road surfaces as well. The force due to the road gradient is:mg sin(tan⁻¹(G))where m is the mass of the car, g is the gravitational constant, and Gis the grade of the road. The force due to the acceleration of the caris ma (the mass of the car times the acceleration over the segment,assuming linear acceleration for the segment).

Putting everything together, the equation can be solved for E, the totalenergy used over the segment. Similar equations are described forcalculating the total energy used over a segment in “The Speed of Light,The 1996 World Solar Challenge” by Roche, Schinckel, Storey, Humphris,and Guelden (UNSW, 1997), herein incorporated by reference in itsentirety.

FIGS. 4A, B describe a method of calculating an array of optimizedvelocities for an entire route that has been broken up into segments. Insome variations, only one or a subset of optimized speeds arecalculated.

Variations on the above equations may be made to simplify therelationships or to include additional factors. For example, the speedvarying part of the rolling resistance equation may be removed tosimplify the equation to: mgC_(rr) cos(tan⁻¹ (G)).

Additional factors could be added as well, for example, by including thevariation of the motortrain efficiency with speed, or by including thevariations of the CdA depending on the directionality of the wind.

4. Historical Route Information

The power management device may refer to a record of historical routeinformation. For example, the power management device may include amemory or a data structure that holds information on routes or segmentsor routes that the vehicle has previously traveled. The memory maycomprise a database, a register, or the like. In some variations, apower management system communicates with a memory or other datastructure that is located remotely. The record of historical routeinformation may include the route information (e.g., starting locationand any intermediate locations), as well as information about the actualor optimized velocities and/or applied power for the vehicle travelingthe route. The record of historical route information may also includeany information from information inputs (described below). For example,the record of historical route information may include information aboutthe time of day, weather conditions, road conditions, driver, etc.Multiple records for the same route (or segments of a route) may beincluded as part of the record of historical route information.

The record of historical route information may provide statisticalinformation on driving habits. The driving habits of an operator over aparticular route or segment of a route may be determined by analyzingthe previous times that the driver has taken this route, and by lookingat the efficiency (e.g., the power efficiency) for each previous trip,and for the combination of previous trips. Thus, the historical routeinformation may be analyzed by statistical route analysis logic that candetermine a probable optimal speed at each point along a route (e.g., atsegments along the route). The more times that a driver has driven theroute, the more data can be used to estimate a probable optimal speedfor all or part of the route.

Historical data may be particularly useful when there is a large amountof such data available. Instead of trying to calculate the predictedpower usage based on physics modeling, this method merely looks at allof the previous data to determine the power that would be utilized todrive each segment at a particular speed. For example, in the past, adriver may have driven a particular segment 1000 times. Out of thosethousand times, she may have driven it at speeds ranging from 80 kph to120 kph. For each of those 1000 times that she drove the segment, thecar recorded how fast she drove it, and how much energy was used.Therefore, to estimate how much energy would be required to drive thesegment at 95 kph, the power may be estimated by taking an average ofall of the previous times the driver drove that segment at 95 kph toarrive at an estimated energy usage, rather than calculating the powerfrom the physics calculations, as described above. In one variation,only the previous trips along the segment made under approximatelysimilar conditions are considered (e.g., similar cargo weight,headwinds, etc.).

FIG. 5 describes one method of using historical data to determine aProbable Optimal Speed. This speed most likely approximates the optimalspeed, based on previous trips. In general, this method is most accuratewhen there are many similar previous trips in the database. FIG. 5 showsthat the location of the vehicle is periodically determined (e.g., viaGPS, manual entry, etc.), and this location can then be used todetermine a historical segment corresponding to the current location. Asdescribed above, every route may be divided into a finite number ofsegments, and the more segments that the route is split into, the moreaccurate the algorithms may be. However, additional segments alsoincrease the computing power needed. The destination is also determinedperiodically 505 (e.g. as the vehicle is moving), and is reevaluatedbased on the current location. It can then be determined if the vehicleis in the same segment as previously determined or if it has entered anew segment 507 since reevaluating the vehicle location. If the answeris “yes,” then nothing needs to be done until the next time the locationis measured. If the answer is “no,” then the database is examined tofind the historical information about this segment. For example, thehistorical information is queried to determine what speed the vehiclewas traveling every time that the vehicle (or the specific driver of thevehicle) was in the same segment going to the predicted destination. Inparticular, the historical information is queried to determine how fastthe vehicle was traveling during the trip in which the vehicle used theleast amount of energy over the same route. The result of this querygives a speed that is most likely the best (e.g., most efficient) speedto travel for the current trip. The process can iteratively repeat forthe next location measurement as the vehicle continues.

FIG. 5 describes a method of determining a probable optimal speed usinghistorical route information. In FIG. 5 , the probable optimal speed isidentified from the historical route information as the most efficientspeed (e.g., the speed having the lowest energy requirement) used by thevehicle when traversing the segment, when that segment is part of aroute having the same destination as the current destination. Theflowchart shown in FIG. 5 illustrates a continuous process, in which thepower management device can determine a probable optimal speed as thecurrent segment changes (e.g., as the vehicle moves).

In some variations, probable optimal speeds may be identified for theentire route. For example, the predicted or actual route may besegmented, and an array of probable optimal speeds may be identifiedfrom the historical route information for each segment. In somevariations, the probable optimal speed is not a single most efficientspeed for a segment of a route, but is derived from a combination (e.g.,an average, median, weighted average, etc.) of all or a subset of thehistorical route information speeds. In some variation, only a subset ofthe historical route information is used. For example the probableoptimal speed may be driver specific, so that only information for aspecific driver is used to calculate a probable optimal speed. Driversmay be identified by bodyweight, or some other information input,including self-identification. If there is no historical routeinformation for the segment or route being examined, then the probableoptimal speed may be set to a predetermined value (e.g., zero), or someother indicator may be toggled so that the probable optimal speed is notrelied upon.

In one variation, a reliability estimate may be assigned to the probableoptimal speed. For example, a reliability estimate may be related to thenumber of data points (e.g., the number of times that the vehicle (or adriver driving the vehicle) has driven that segment or route. Forexample, if there are no records of the vehicle driving the route, thereliability estimate may be set very low. Generally, the more recordsfor a route in the historical route information, or the more closely theidentifying information in the record matches the information about thecurrent route (e.g., the driver, weather conditions, traffic, etc.), thehigher the setting of the reliability estimate.

5. Calculation of an Efficient Speed Output

Finally, an efficient speed for the vehicle to travel the route (or apart of the route) may be determined from the calculated optimized speedand the probable optimal speed. The optimum speed is the most efficientspeed (E), as described above. This efficient speed (or efficient speedoutput of the power management system) may also be expressed as theapplied power that is provided to the engine to achieve the speed atwhich the fuel efficiency is optimal. Thus, an efficient speed istypically a function of the driver's current operational demands, thecurrent operational conditions of the vehicle, the operationalparameters for the vehicle, and any historical behavior of the vehicletaking the same (or a similar) route.

In general, an efficient speed output is determined by a combination ofthe calculated optimized speed and the probable optimized speed afterthey have been appropriately weighted. In some variations, thisweighting takes into account the total energy predicted by thecalculated optimized speed (e.g., by the simulated energy requirementlogic) and the total energy required for the route predicted by theprobable optimized speed (e.g., by the statistical route analysislogic). The reliability estimate for the probable optimized speed mayalso contribute to the weighting. The power management device mayinclude derived efficient speed logic that can determine efficientspeeds for the vehicle to travel the route, or a portion of the route.In some variations, the efficient speeds are expressed as power orenergy to be applied to the vehicle engine (e.g., the applied power).

As previously mentioned, the methods and logic described above may beused to calculate a speed or an applied power for running the vehicle atan optimal fuel efficiency. As will be apparent to one of skill in theart, the same procedures may be used to determine a speed (or speeds)over the route that minimize or maximize other factors, and are notlimited to optimizing only fuel efficiency. For example, the powermanagement device may control the speed of the vehicle so as to minimizethe duration of the trip instead of (or in addition to) fuel efficiency.Thus, the simulated energy requirement logic may be expressed as asimulated time requirement, and may calculate the time required totravel a segment of the route as a function of the speed or energy, andadditional information input. In this case, calculated optimized speedsmay be determined by minimizing the duration of the trip over eachsegment. Furthermore, the probable optimal speed may be determined fromthe historical route information based on the duration of travel, ratherthan the power applied, for each segment.

Control Logic

The power management device may include control logic for controllingthe operation of the power management device. Control logic may includelogic for acquiring information inputs, communicating with differentcomponents of the power management system, estimating the destination ofthe vehicle from information inputs, segmenting the route into segments,simulating the energy requirements of the engine from informationinputs, and controlling the entire power management device or system.

For example, the power management device or system may include pollinglogic for acquiring information inputs and may also coordinate writingof information from the power management device to a memory. In somevariations, the polling logic polls sources of information data that areprovided to the power management device. For example, the polling logicmay poll data from sensors, inputs, memories, or any other source ofinformation data. The polling logic may further coordinate storing ofthis data in a memory, such as a memory register or a memory device ordatabase that may be accessed by the power management device or system.In some variations, the polling logic causes old data (e.g., greaterthan x weeks old) to be overwritten. The polling logic may also controlhow often the various information data sources are polled. For example,the polling logic may continuously poll data from external environmentalsensors (e.g., detecting location, direction, elevation, traffic,weather, etc.) and operational status detectors (e.g., detecting vehiclespeed, well velocity, motor speed, etc.). The polling logic may alsocoordinate writing of route information. For example, the polling logicmay coordinate recording the decisions made at intersections, andinformation about routes traveled by the vehicle, and the like. In somevariations, the polling logic also coordinates the writing ofinformation derived from the information inputs to a memory. Forexample, the polling logic may coordinate recording the optimal speed orenergy used to traverse a segment or other portion of a route.

As described above, the power management device or system may alsoinclude statistical destination logic. Statistical destination logic mayinfer one or more likely destinations based on the information inputs.For example, the power management system may infer the destination ofthe route based on the current location and direction of the vehicle,and the date and time of day. In some variations, the power managementsystem is unable to infer a final destination, but it can generate anintermediate destination or segment for the route, as described above.The probable destination(s) identified by the statistical destinationlogic may then be used to optimize the power needed to travel the routeor a segment of the route, and to determine a historical probableoptimal speed.

In some variations, the power management device or system includessimulated energy requirement logic and statistical route analysis logic.As described above, simulated energy requirement logic may determine acalculated optimized speed for the vehicle, and statistical routeanalysis logic may be used to determine a probable optimal speed. Thepower management device or system may also include derived efficientspeed logic that determines the most efficient speed or power to beapplied to the vehicle engine, as described above.

Power management logic can coordinate different components of the powermanagement system, including the logic components, user interfaces,informational data inputs, memory, processors, motor control mechanisms,and the like. Thus, the power management system may include powermanagement logic to control the overall activity of the power managementsystem. FIG. 6 shows a graphical representation of one variation of thepower management device, indicating that the power management logiccontrols and coordinates the various components of the system. In FIG. 6, the polling logic 607 coordinates the activity of information inputs601, 603, 605. The information inputs are also linked to each other andto the statistical destination logic 609, statistical route analysislogic 611, and simulated energy requirement logic 613. In particular,these elements are all connected to the memory, and may read and writeto this memory. The derived efficient speed logic also controls thesethree logic elements 609, 611, and 613. As described above, the derivedefficient speed logic 615 may produce an efficient speed output for eachpart of the route (e.g., the speeds or applied powers resulting fromoptimizing the fuel efficiency over the route or parts of the route).Before this applied power can be used to control the motor (via a motorcontrol mechanism 619), the power management logic may check foroverrides such as operator overrides (e.g., braking), or other overridesthat may be indicated by the headway cruise control box 617. Forexample, the operator may override the power management device byapplying the brakes, etc. The power management device may also bepreempted by an obstruction (such as another vehicle) in the “headway”that blocks the vehicle, requiring the vehicle to slow or stop.

FIG. 6 shows one variation of the power management device descriedherein. As will be apparent to those of skill in the art, differentvariations are possible. For example, additional components (e.g.,communications elements, microprocessors, memories, etc.), and/oradditional logic (e.g., route segmentation logic, operator interfacelogic, etc.) may also be included. In some variations, some of theelements may be omitted (e.g., the separate polling logic), or may becombined with other elements. In some variations, the organization ofthe elements may be different. For example, the statistical destinationlogic may be controlled by the polling logic, rather than the derivedefficient speed logic.

Power Management Devices

In general, the power management device comprises power management logicthat receives information input about the external environment of thevehicle, the operational status of the vehicle, one or more commandinputs from the driver, and one or more operational parameters of thevehicle. The power management device may also include additionalcomponents such as information inputs (e.g., sensors, detectors, relays,etc.), one or more processors (e.g., microprocessors), memories (e.g.,databases, ROM, RAM, EPROM, etc.), communications devices (e.g.,wireless connections), user interfaces (e.g., screens, control panels,etc.), and/or motor control mechanisms. In some variations, the powermanagement device may be installed into the vehicle by the vehiclemanufacturer. In other variations, the power management device may beretrofitted into a vehicle. In general, the power management device orsystem intervenes between the driver and the engine. In practice, thepower management system may be physically located in any appropriatelocation in the vehicle. FIG. 7 shows one example of a vehicle having apower management system 701 as described herein. In FIG. 7 , the powermanagement system is shown in the front of the car 700, connecting themotors 705 and batteries 707.

Any appropriate sensors, detectors or data inputs may be used with thepower management devices and systems described herein. For example,sensors for detecting external environmental information may be used(e.g., optical, mechanical, electrical, or magnetic sensors). Sensorsmay be monitored (e.g., polled) in real-time, as described above. Forexample, polling logic may coordinate continuous or periodic polling ofGlobal Positioning System (GPS) information (e.g., giving information onthe vehicle's current location, current elevation, upcoming elevations,upcoming terrain, vehicle's destination, etc.), speedometer information(e.g., vehicle's current speed, motor speed), date and time information(e.g., the date and time may be used to determine personal drivinghabits and sun angle), gyroscope information (e.g., vehicle's currentorientation, current slope/grade of road), RPM (e.g., motor and wheelrotations per minute), accelerator and brake pedal position (e.g.,pressure applied and/or current angle of the pedals), the angle of thesun (e.g., sensors may detect latitude, longitude, time of day, date),weather (e.g., wind direction and velocity, rain, sun, snow, etc.),battery state (e.g., voltage, amp hour meter, etc.), tire pressure(e.g., may be used to calculate the drag force due to rollingresistance), headway control information (e.g., the distance from a carin front of the vehicle), the weight of car (e.g., weight of cargo,passengers, driver), airflow (e.g., the amount of air going to theengine), gas flow sensor (e.g., the amount of gas going to engine of ahybrid or ICE car), and weight of the driver (e.g., may be used identifythe driver and may be linked to personal driving habits). Differentdetectors or sensors may be polled at different intervals, includingcontinuously, or only occasionally. Polling may also depend upon theavailability of a resource. For example, information may be availableonly when a telecommunications network (e.g., satellite, cellular, etc.)is available.

In some variations, a memory may be used. The memory may be read/writememory, or read only memory. The memory may include information, such asinformation on the operational parameters of the vehicle related to themake and model of the vehicle. As described above, operationalparameters may include look up tables, charts, or the like. For example,a memory may include information about an aerodynamic model (CDA) forthe vehicle, a rolling resistance model (Crr1 and Crr2), a drive trainefficiency model, a motor efficiency model, and/or a battery model(e.g., charge and discharge graphs for the battery). In some variations,these models are not part of a memory, but are algorithms or logic.

Any appropriate memory may be used, including ROM, RAM, removablememories (e.g., flash memory), erasable memories (e.g., EPROM), digitalmedia (e.g., tape media, disk media, optical media), or the like. Insome variations, the memory may comprise a database for holding any ofthe route information (including historical route information), aboutthe segments traveled, the speeds traveled, energy usage measured orcalculated for this route or segment, who the driver was, externalenvironmental conditions while driving the route, operational status ofthe vehicle while driving the route, and command inputs while drivingthe route. The power management system may include more than one memory.

The power management system may also include one or more userinterfaces. A user interface may allow input of user command information(e.g., selecting a destination, selecting a route, selecting a targetspeed or speeds, selecting a range of acceptable speeds, etc.). In somevariations, a user interface may also provide output from the powermanagement system that can be viewed by the user. For example, the userinterface may provide visual or auditory output, or suggest targetspeeds that the user can match to optimize power supplied to thevehicle. In some variations the user interface may provide statusinformation to the user about the power management system. For example,the user interface may indicate that the power management system isengaged, what the destination (or predicted destination) is, what theoptimal speed (or speeds) is, what inputs are missing or estimated, orthe like. In some variations, the user interface may display any of theinformation inputs.

FIG. 8 shows one variation of a user interface for a power managementdevice or system. In FIG. 8 , the user interface 800 includes a screenregion 801, that shows a two-dimensional map indicating at least part ofthe route 805 and the direction of travel 803, the temperature of theexternal environment 807, the weather 809 (indicated by an icon), thecurrent or derived efficient speed 811, the set (or cruising) speed 813,and the range within which the speed should be maintained 815. Thescreen region of the user interface shown in FIG. 8 also shows thedestination 819.

In some variations, the user interface of the power management systemmay include multiple screens for displaying information, or foraccepting user input. In FIG. 8 , the user interface also includes aplurality of buttons 821, including a toggle 823 allowing menu-driveninteraction. The user interface may also include messaging features. Forexample, when the vehicle is turned on but stopped, a user interface mayindicate a message has been sent/received (e.g., by flashing, etc.).When the user presses a “Messages” button, the system may displayfeedback messages. For example, if the tire pressure sensor notices thatthe tire pressure is low, a message to that effect will be displayed tothe user. Diagnostic/test messages can also be sent to this screen fortesting, development, or repair purposes. The messaging features may beincluded on the face of the user interface (e.g., as a “Messages” button821, etc.).

FIG. 9 illustrates the flow of information in one variation of a powermanagement system. Information inputs into the power management system901, 903, 905 enter the system and some (or all of them) may bedisplayed by the user interface. For example, external informationinputs 901 may be shown. The status of some of the information inputs(or the status of the detectors that receive the information inputs) mayalso be shown. For example, the user interface can indicate when thesystem is connected to an external information input. In somevariations, the external information inputs may be connected to thepower management system by a wireless transmission (e.g., from anexternal source), and the connection to the external source may beindicated by the user interface. As described above, the user interfacemay accept command inputs from the driver (or a passenger) 905. In somevariations, user commands may be accepted directly by using buttons onthe user interface, or by voice commands. In other variations, at leastsome of the user commands may be entered into the power managementsystem from another source (e.g., a separate cruise control or GPSdevice). Finally, the user interface may indicate the output of thepower management device or system 909, typically an efficient speedoutput for the engine.

In some variations, the power management system may include a headwaycruise control. The headway cruise control can prevent collisions whenthe vehicle is in motion by overriding the power management controlsystem's control of the vehicle speed. In some variations, the headwaycruise control detects the proximity of other vehicles or obstacles inthe road ahead. The headway cruise control may include sensors on thevehicle, such as laser, ultrasound or other electronic distancemeasurement devices. Increasingly, more vehicles are including some sortof GPS interface to communicate with other vehicles to determinedistance between the vehicles to avoid collisions.

The power management devices and systems described herein may alsoinclude a motor control mechanism. The motor/engine controller changesthe motor speed by mechanical operations such as pulling on a cable toadjust gas/airflow mixture or by electrical means with either analog ordigital inputs by the driver. With electric driven motors, a variablemay be changed to increase or decrease motor speed. In the cruisecontrol settings, the speed of the motor may change based on analgorithm in the processor.

The power management devices and systems described herein may beorganized in any appropriate manner, as described above. For example, insome variations, the power management device described herein mayinclude component parts that are connected as illustrated in FIG. 10 .FIG. 10 shows a schematic of one variation of a power management device.In FIG. 10 , the power management system includes a central processor1001 (CPU) that can execute control logic such as power managementcontrol logic, statistical destination logic, simulated energyrequirement logic, statistical route analysis logic, derived efficientspeed logic, polling logic, etc. This CPU receives inputs from sensors1005, GPS receiver 1007, a clock 1011, a telemetry data receiver 1009, aspeech recognition processor 1021 (including a microphone 1019, 1025),user interface buttons 1039, 1037, and memory components (including RAM1035, a long-term memory 1033, firmware ROM 1031, and a removable memory1029, 1041). The CPU may also coordinate output through the LCD display1015, 1017, a speaker 1023, 1027, and the motor control mechanism (motorcontroller) 1043. In some variations, the sensors 1045 may also beincluded as part of the power management devices or systems.

As described above, the power management system may also be used with atelemetry system. Thus, the power management system may communicate withone or more external components. For example, the power managementsystem may store information in a remote memory. The power managementsystem may also contribute to a database of information about route,road conditions, and the like, such as a database of historical routeinformation. In some variations, the motor control system may remotelycommunicate with a processor, so that at least some of the control logicis applied remotely.

FIG. 11 shows a schematic illustrating the use of telemetry by the motorcontrol system. In FIG. 11 , a power management device 1101 communicatesby wireless communication with a database 1107 through atransmitter/receiver 1105 (shown as a satellite). Any reasonable type ofwireless communications may be used, including cellular, wirelessinternet connections, radio, or the like. In this example, the databasemay both receive data from the power management device and/or transmitdata or instructions to the power management device. Communicationbetween the power management device and other components that areremotely located (e.g., memory, processor, information inputs) may alsobe used to update or correct the power management device. For example,the operational parameters of the vehicle may be revised or updated froma remote source. In some variations, control logic (e.g., powermanagement control logic) may be remotely updated or revised.

The concepts described above may be used in various combinations tooptimize the power used by a vehicle. Examples of power managementsystems, including methods of using them, are described below.

EXAMPLES

1. Fuel Efficient Hybrid Vehicle

Using one variation of the power management system described herein(e.g., a power management system having an integrated GPS), a hybrid carapproaching a large hill or grade can adjust the ratio of electric toICE such that the batteries would be empty at the crest of the hill andfully charged at the bottom of the hill, and therefore would use lessgasoline.

The same methods described above could be used to calculate the energyusage of the vehicle as in the previous example. The mix of electric toICE can be based on the calculated energy usage and the energy stored inthe batteries. The exact mechanism for instructing the hybrid vehicle toalter its electric/ICE ratio may vary between manufacturers.

2. Fuel Efficient Internal Combustion Engine (ICE) Vehicle

Using one variation of the power management system described herein, anICE car will speed up on a downhill when it knows that an uphill is thenext terrain, and thereby use momentum to get up the hill, using lessgasoline. FIG. 1B illustrates this Example. As described previously, thesystem may determine the optimum energy using external and internalsensors and information, including the operational parametersappropriate to the vehicle. Such operational parameters may vary frommanufacturer to manufacturer (or vehicle to vehicle), and, as describedabove, could involve sending an electrical signal to a computer-basedmotor controller or even mechanically controlling the gas/air-flowmixture to the engine.

3. Energy Efficient Solar-Powered Vehicle

Using one variation of the power management system described herein, asolar-powered car can ensure that it has adequate power to traverse apredetermined route. The power management system may ensure that thereis enough solar energy power for the route by slowing and speeding thecar as necessary based on current energy levels and anticipated energyneeds.

This example is similar to the example discussed when determining theoptimum speed above, with a couple of additional steps. In addition tocalculating the energy usage, the system may also include a solar arraymodel that could model the power generated by the solar array throughoutthe route base on the predicted weather, geographic location, and timeof day. A battery model may also be included to keep track of the energyput into the batteries by the solar array and the energy drawn from thebatteries by the motor. When selecting the optimum speeds to drive thesegments of the route, the system logic (e.g., software, hardware orboth), may apply or access the battery model to prevent the battery frombecoming completely drained.

4. Preventing Engine Flooding

One of the keys to efficient driving is not to step on the acceleratormore than the engine can actually burn and use efficiently. Flooding theengine not only wastes gas but it doesn't maximize power, despite thedriver's demands. According to one variation of the power managementsystem described herein, a traditional ICE engine may be protected fromflooding of the engine using the power management device.

In this variation of a power management device, power management devicereceives information inputs including a command input (acceleration), atleast two environmental inputs (air resistance), the operational statusof the vehicle (velocity and engine temperature), and at least oneoperational parameter (e.g., maximum fuel volume). For example, thepower management device may receive information about the amount ofpressure that the driver is applying to the accelerator. The powermanagement system may also detect the current speed, resistance andtemperature of the vehicle. This information input may be used to selectthe proper operational parameter of the vehicle. For example, the devicemay include a memory having a table of maximum fuel volumes for a givenvelocity, resistance and temperature. Thus, the velocity, resistance andtemperature data may be used to look up a maximum fuel volume. In somevariations, the maximum fuel volume may be calculated or estimated fromthis data. By comparing the operator demand (for acceleration) to supplyfuel with the maximum amount of fuel that the engine can handle, thepower management control logic may correct for the driver'sinefficiency, and instruct the motor control mechanism to provide theactual maximum amount of fuel to the engine, thereby avoiding floodingof the engine.

This last example is a very simplified case of the overall actions ofthe power management control system. In general, the power managementdevice intervenes between the driver and the engine. Thus, the powermanagement device may interpret the driver commands so that the drivingobjective is achieved while maximizing the efficiency of the vehiclebased on information that is not generally accessible or interpretableby the driver. While the invention has been described in terms ofparticular variations and illustrative figures, those of skill in theart will recognize that the invention is not limited to the variationsor figures described.

For example, in one variation the system would be able to notify thedriver of the most fuel efficient speed for a route segment or segmentdestination. The notification might be via voice, written word, numbers,symbols, colors and/or the like. The vehicle operator can then manuallyadjust the vehicle speed in response to the notification. In thisexample, the calculated power would not necessarily be directly appliedto the vehicle engine as it would just be used as a driver alert.

In still another variation, the power consumption calculation couldfurther include or be based on calculating an optimal acceleration to(gradually) accelerate to the determined efficient speed to travel thesegment destination or optimal deceleration to (gradually) decelerate tothe determined efficient speed to travel the segment destination. Thecalculation could for example incorporate GPS information, thedetermined efficient speed to travel the segment destination, or acombination thereof.

In still another variation, the information could be based on pasthistory information of the vehicle, information of one or more othervehicles traveling one or more of the same route segments, or acombination thereof. For example, if one drives the same route to workeach day, the energy consumption of those various trips can be storedalong with the speeds driven along different segments of the route. Fromenough historical data, an optimized route could be determined.

In still another variation, the information could be stored informationof vehicles traveling overlapping route segments. If many cars drivealong overlapping segments, their energy usage for those segments couldbe uploaded to e.g. a centralized server where optimized speeds forthose segments could be calculated. Those optimized speeds could beshared in several ways such as, but not limiting to, (i) transmitteddirectly to cars, where they could be used in fuel economy optimizingcruise control, (ii) transmitted to cars where they could be used toprovide recommendations to drivers, (iii) shared via a web site wheredrivers could view recommendations, (iv) shared via a web site wheredrivers could compare their fuel economy to that of other drivers. Thedata could be used by state or local governments to adjust speed limitsto improve the overall fuel economy of the cars that drive along theirroads.

In still another variation, an automatic transmission vehicle could usethe determined efficient speed to intelligently shift gears, i.e., theoptimized speed for (upcoming) route segments could be used by theautomatic transmission to make intelligent decisions about shiftinggears which would improve overall drive train efficiency.

In addition, where methods and steps described above indicate certainevents occurring in a certain order, those of skill in the art willrecognize that the ordering of certain steps may be modified and thatsuch modifications are in accordance with the variations of theinvention. Additionally, certain steps may be performed concurrently ina parallel process when possible, as well as performed sequentially asdescribed above. Therefore, to the extent there are variations of theinvention, which are within the spirit of the disclosure or equivalentto the inventions found in the claims, it is the intent that this patentwill cover those variations as well. Finally, all publications andpatent applications cited in this specification are herein incorporatedby reference in their entirety as if each individual publication orpatent application were specifically and individually put forth herein.

What is claimed is:
 1. A method for optimizing a travel time of avehicle to a destination, comprising: using one or more processors: (A)monitoring a plurality of sensors to generate sensor data samples duringoperation of a vehicle; (B) storing said sensor data samples formultiple points in time along a route segment traveled by said vehicle;(C) analyzing said sensor data samples to detect a historical pattern ofsaid vehicle; and (D) determining time-power efficient operationalparameters for said vehicle in response to (a) a destination, (b) anestimated travel time to said destination, and (c) an estimated powerconsumption, wherein said estimated travel time is based on predictedconditions of said vehicle indicated by said historical pattern, (ii)said time-power efficient operational parameters are selected to balancebetween reducing the estimated travel time and reducing the estimatedpower consumption, and (iii) at least one of said sensor data samplescomprises telemetry data.
 2. The method of claim 1, wherein theestimated power consumption is based on historical data related tosensed energy consumption of the vehicle while traveling on a routemultiple times.
 3. The method of claim 1, further comprising, using theone or more processors, determining a probable optimal speed for aroute, configured to reduce an amount of power consumed by the vehicle,at least in part by determining what speed the vehicle was travelingalong the route during a trip in which the vehicle used a least amountof energy traveling the route.
 4. The method of claim 1, furthercomprising, using the one or more processors, determining a probableoptimal speed for a route, configured to reduce an amount of powerconsumed by the vehicle, and assign a reliability estimate to theprobable optimal speed related to a number of times the vehicle hasdriven the route.
 5. The method of claim 1, further comprising, usingthe one or more processors, determining a probable optimal speed for aroute, configured to reduce an amount of power consumed by the vehicle,using only a subset of historical speeds for the route.
 6. The method ofclaim 1, further comprising, using the one or more processors,determining a probable optimal speed for a route, configured to reducean amount of power consumed by the vehicle, wherein the probable optimalspeed is derived using one of an average, a median, and a weightedaverage of a plurality of historical speeds associated with the route.7. The method of claim 1, further comprising, using the one or moreprocessors, determining an energy efficient speed, configured to reducean amount of power consumed by the vehicle, by minimizing power requiredby the vehicle while allowing a speed of the vehicle to vary within arange of predetermined acceptable speeds.
 8. The method of claim 1,further comprising, using the one or more processors, determining anenergy efficient speed, configured to reduce an amount of power consumedby the vehicle, by determining a speed closest to a desired speed atwhich the amount of power consumed by the vehicle is lowest.
 9. Themethod of claim 1, further comprising, using the one or more processors,determining a plurality of probable optimal speeds, including at leastone probable optimal speed for each of a plurality of segments of aroute, the plurality of probable optimal speeds configured to reduce anamount of power consumed by the vehicle while traveling the route.
 10. Avehicle, comprising: a power train; a sensor interface configured toreceive sensor data samples during operation of said vehicle; a storagedevice configured to store said sensor data samples for multiple pointsin time along a route segment traveled by said vehicle; and one or moreprocessors configured to (i) analyze said sensor data samples stored insaid storage device to detect a historical pattern of said vehicle and(ii) determine time efficient operational parameters for said vehicle inresponse to (a) a destination and (b) an estimated travel time to saiddestination, wherein (i) said estimated travel time is based onpredicted conditions of said vehicle indicated by said historicalpattern, (ii) said time efficient operational parameters are selected todecrease said estimated travel time and (iii) at least one of saidsensor data samples comprises telemetry data.
 11. The vehicle of claim10, wherein said destination is determined based on said historicalpattern.
 12. The method of claim 10, wherein said historical patterncomprises at least one of an identity of a driver, a route andenvironmental conditions.
 13. The method of claim 10, wherein said timeefficient operational parameters comprise a sequence of route segmentsto reach said destination, an amount of power consumed by said vehicleand a travel speed.
 14. The method of claim 10, wherein the vehicle isfurther configured to communicate with a remote database and said remotedatabase is configured to store historical route information for aplurality of route segments corresponding to said telemetry data. 15.The method of claim 14, wherein said historical pattern furthercomprises said historical route information for said plurality of routesegments.
 16. The method of claim 14, wherein said historical routeinformation comprises previously stored conditions associated with eachof said plurality of route segments.
 17. The method of claim 10, whereinsaid predicted conditions comprise at least one of: drag, windresistance, tire resistance, an amount of light energy, a position ofthe sun, an elevation of said vehicle, a location of stoplights, atiming of stoplights, weather, a wind direction, a wind velocity, atemperature, air pressure, moisture, visibility, an amount of vibration,a fuel supply, a battery supply, a condition of tires of said vehicle, acondition of a motor of said vehicle, a condition of a powertrain ofsaid vehicle, and traction.
 18. The method of claim 10, wherein thevehicle is further configured to communicate said time efficientoperational parameters to a remote database and said remote database isconfigured to provide guidance information to a fleet of vehicles.
 19. Asystem for optimizing travel time of a vehicle, comprising: a sensorinterface configured to receive sensor data samples during operation ofa vehicle; a storage device communicatively coupled with the sensorinterface and configured to store said sensor data samples for multiplepoints in time along a route segment traveled by said vehicle; and oneor more processors communicatively coupled with the storage device andconfigured to (i) analyze said sensor data samples stored in saidstorage device to detect a historical pattern of said vehicle and (ii)determine time efficient operational parameters for said vehicle inresponse to (a) a destination and (b) an estimated travel time to saiddestination, wherein (i) said estimated travel time is based onpredicted conditions of said vehicle indicated by said historicalpattern, (ii) said time efficient operational parameters are selected todecrease said estimated travel time and (iii) at least one of saidsensor data samples comprises telemetry data.
 20. The system of claim19, wherein the time efficient operational parameters are based onhistorical data related to sensed energy consumption of the vehiclewhile traveling on a route multiple times.